Yang Li's research while affiliated with Jining Medical University and other places

Background Acute kidney injury (AKI) is a common and serious condition, particularly among elderly patients. It is associated with high morbidity and mortality rates, further compounded by the need for continuous renal replacement therapy in severe cases. To improve clinical decision-making and patient management, there is a need for accurate prediction models that can identify patients at a high risk of mortality. Methods Data were extracted from the Dryad Digital Repository. Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) logistic regression analysis to identify independent risk factors and construct a predictive nomogram for mortality within 28 days after continuous renal replacement therapy in elderly patients with acute kidney injury. The discrimination of the model was evaluated in the validation cohort using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using a calibration curve. The clinical utility of the model was assessed using decision curve analysis (DCA). Results A total of 606 participants were enrolled and randomly divided into two groups: a training cohort (n = 424) and a validation cohort (n = 182) in a 7:3 proportion. A risk prediction model was developed to identify independent predictors of 28-day mortality in elderly patients with AKI. The predictors included age, systolic blood pressure, creatinine, albumin, phosphorus, age-adjusted Charlson Comorbidity Index (CCI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and sequential organ failure assessment (SOFA) score. These predictors were incorporated into a logistic model and presented in a user-friendly nomogram. In the validation cohort, the model demonstrated good predictive performance with an AUC of 0.799. The calibration curve showed that the model was well calibrated. Additionally, DCA revealed significant net benefits of the nomogram for clinical application. Conclusion The development of a nomogram for predicting 28-day mortality in elderly patients with AKI receiving continuous renal replacement therapy has the potential to improve prognostic accuracy and assist in clinical decision-making.

Background Chromatin modified protein 4C (CHMP4C) is a charged polyvesicular protein (CHMP) that is involved in the composition of the endosomal sorting complex (ESCRT-III) required for transport III and promotes the necessary separation of daughter cells. CHMP4C involved in a wide variety of tumor progress,, such as prostate cancer, cervical cancer and lung squamous cell carcinoma. However, the value of CHMP4C in lung adenocarcinoma has not been explored. Methods RNA-seq data and lung adenocarcinoma clinical information and corresponding pan-cancer were extracted from The Cancer Genome Atlas (TCGA) database to analyze CHMP4C expression and survival prognosis. The differential expression of CHMP4C was analyzed using the Human Protein Atlas (HPA) database. Clinical samples were collected to verify the differential expression of CHMP4C between lung adenocarcinoma and normal lung tissues via immunohistochemical (IHC) staining, qRT‒PCR and Western blotting. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of CHMP4C-related genes were performed. The correlation between CHMP4C and chemosensitivity was analyzed in the TCGA database. Then, qRT‒PCR, western blotting, transwell assays, cell proliferation assays, colony formation assays, wound healing assays, and cell cycle analysis were used to verify the possible regulatory mechanism involved. Molecular docking was used to predict small molecule compounds with potential roles in the treatment of lung adenocarcinoma. Results TIMER2.0 database analysis revealed that CHMP4C was differentially expressed in different tumors.Compared with that in healthy lung tissue, CHMP4C was significantly upregulated in lung adenocarcinoma tissue, and subsequent in vitro survival analysis revealed that CHMP4C expression has significant clinical prognostic value in lung adenocarcinoma. Enrichment analysis revealed that CHMP4C was mainly related to cell proliferation, cell migration, and the PI3K-Akt signaling pathway, etc. Overexpression of CHMP4C was associated with sensitivity to chemotherapy. Knocking down CHMP4C can significantly inhibit the proliferation, migration and invasion of lung adenocarcinoma cells and prolong the G0/G1 phase of the cell cycle. Molecular docking predicts 10 key drugs that may be used for the treatment of lung adenocarcinoma. Conclusions CHMP4C is highly expressed in a variety of tumors.We demonstrated that CHMP4C expression may be associated with the occurrence, development, prognosis and chemotherapy sensitivity in patients with lung adenocarcinoma. These findings may open up new research directions and development opportunities for the treatment of lung adenocarcinoma.

Gastric cancer (GC) is one of the most common gastrointestinal tumors. As a newly discovered type of non-coding RNAs, transfer RNA (tRNA)-derived small RNAs (tsRNAs) play a dual biological role in cancer. Our previous studies have demonstrated the potential of tRF-23-Q99P9P9NDD as a diagnostic and prognostic biomarker for GC. In this work, we confirmed for the first time that tRF-23-Q99P9P9NDD can promote the proliferation, migration, and invasion of GC cells in vitro. The dual luciferase reporter gene assay confirmed that tRF-23-Q99P9P9NDD could bind to the 3′ untranslated region (UTR) site of acyl-coenzyme A dehydrogenase short/branched chain (ACADSB). In addition, ACADSB could rescue the effect of tRF-23-Q99P9P9NDD on GC cells. Next, we used Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to find that downregulated ACADSB in GC may promote lipid accumulation by inhibiting fatty acid catabolism and ferroptosis. Finally, we verified the correlation between ACADSB and 12 ferroptosis genes at the transcriptional level, as well as the changes in reactive oxygen species (ROS) levels by flow cytometry. In summary, this study proposes that tRF-23-Q99P9P9NDD may affect GC lipid metabolism and ferroptosis by targeting ACADSB, thereby promoting GC progression. It provides a theoretical basis for the diagnostic and prognostic monitoring value of GC and opens up new possibilities for treatment.

Background: Gastric cancer (GC) is one of the malignant tumors with the highest mortality rates worldwide, yet there is a lack of diagnostic markers with high sensitivity in the clinic. tRNA-derived small RNAs (tsRNAs) are a novel type of non-coding small RNAs characterized by their abundance in body fluids and specific biological functions. In this study, we focused on the potential of tsRNAs as biomarkers for the diagnosis of GC. Methods: Differential expression of tsRNAs was screened by high-throughput sequencing, and Quantitative real-time PCR verified the expression of 3′-tRFArg in GC serum and tissues. The methodological evaluation of 3′-tRFArg was confirmed using Sanger sequencing and agarose gel electrophoresis. The correlation between the expression levels of 3′-tRFArg and clinical pathological parameters was analyzed using Chi-square tests. The diagnostic value was assessed through the receiver operating characteristic curve, and the impact of 3′-tRFArg expression on survival was evaluated using Kaplan–Meier survival analysis. Result: 3′-tRFArg was found underexpressed in GC tissues and serum with good stability. The differential expression of serum 3′-tRFArg could identify GC patients and show significant correlations with clinical pathological features. Furthermore, the receiver operating characteristic curve indicated that 3′-tRFArg possesses a higher diagnostic value than conventional biomarkers, particularly in the early diagnosis of GC. Conclusions: 3′-tRFArg is significantly underexpressed in the serum of GC patients and can serve as a biomarker of high sensitivity. It possesses superior diagnostic efficacy compared to traditional markers and is valuable for monitoring tumor development and prognosis.

Objective In most cases, patients with hepatocellular carcinoma (HCC) develop advanced disease when diagnosed. Finding new molecules to combine with traditional biomarkers is crucial for HCC early diagnosis. In cancer development, tRNA-derived small RNAs (tsRNA) play a crucial role. Here, we aimed to identify a novel biomarker among tsRNAs that can facilitate HCC diagnosis and monitor its prognosis. Methods We screened candidate tsRNAs in 3 pairs of HCC and adjacent tissues through high-throughput sequencing. tRF-33-RZYQQ9M739P0J was screened in tissues, sera, and cells through quantitative real-time polymerase chain reaction (qRT-PCR) for further analysis. tRF-33-RZYQHQ9M739P0J was characterized using agarose gel electrophoresis, Sanger sequencing, and nuclear and cytoplasmic RNA isolation. Experiments at room temperature and repeated freeze-thaw cycles were conducted to evaluate the detection performance of tRF-33-RZYQHQ9M739P0J. We measured the levels of differential expression of tRF-33-RZYQHQ9M739P0J in sera using qRT-PCR. We applied the chi-square test to evaluate the correlation between tRF-33-RZYQHQ9M739P0J expression levels and clinicopathological features, and assessed its prognostic value by plotting Kaplan-Meier curves. The diagnostic efficacy of tRF-33-RZYQHQ9M739P0J was evaluated using the receiver operating characteristic (ROC) curve. Finally, the downstream genes related to tRF-33-RZYQHQ9M739P0J were explored through bioinformatics prediction. Results tRF-33-RZYQHQ9M739P0J was highly expressed in HCC tissues and sera, and its expression was correlated with metastasis, TNM stage, BCLC stage, and vein invasion. Expression of tRF-33-RZYQHQ9M739P0J were decreased after surgery in patients with HCC. High serum tRF-33-RZYQHQ9M739P0J levels are associated with low survival rates, and they can predict survival times in patients with HCC according to the Kaplan-Meier analysis. Combining tRF-33-RZYQHQ9M739P0J with serum alpha-fetoprotein and prothrombin induced by vitamin K absence II can improve the diagnostic efficiency of HCC, suggesting its potential as a biomarker for HCC. Conclusion tRF-33-RZYQHQ9M739P0J may not only be a promising non-invasive marker for early diagnosis, but also a predictor of liver cancer progression.

Gastric carcinoma (GC) is a malignant tumor that is detrimental to human health. Transfer RNA‐derived small RNAs are a newly identified class of noncoding small RNAs with specific biological functions that are aberrantly expressed in cancer. The aim of this study was to investigate the potential of hsa_tsr013526 as a biomarker for GC. Quantitative real‐time fluorescence polymerase chain reaction was used to detect the expression level of hsa_tsr013526. The molecular characteristics of hsa_tsr013526 were verified by agarose gel electrophoresis, Sanger sequencing, and separation of nuclear and cytoplasmic RNA fractions. By testing the receiver operating characteristic (ROC) curves, the diagnostic efficiency of GC using hsa_tsr013526 was determined. Finally, we predicted the downstream of hsa_tsr013526 using functional assays and bioinformatics analysis. Serum expression of hsa_tsr013526 was higher in GC patients than in healthy donors. Serum expression showed differential changes in GC patients, gastritis patients, and healthy donors. Chi‐squared tests showed that high expression of hsa_tsr013526 was significantly correlated with T stage, lymphatic metastasis, and tumor node metastasis stage. ROC curve analysis indicated that GC patients could be discriminated from healthy donors or gastritis patients based on their serum levels of hsa_tsr013526. Furthermore, hsa_tsr013526 expression was significantly reduced in postoperative GC patients ( p = .0016). High expression of hsa_tsr013526 promotes gastric cancer cell proliferation, invasion, and migration. Serum hsa_tsr013526 was stable and specific, and could be used for dynamic monitoring of GC patients. Therefore, hsa_tsr013526 may be a new biomarker for the diagnosis and postoperative monitoring of GC patients.

Objective: Gastric cancer (GC) has high morbidity and mortality due to inefficient early screening. Therefore, we are searching for more sensitive and specific diagnostic markers for GC. tRNA-derived small RNAs are novel non-coding small RNAs with good abundance and stable presence in body fluids, which may play multiple biological regulatory roles. In this study, we aimed to find a potential biomarker with high accuracy in tRNA-derived small RNAs that can help diagnose GC. Methods: tRF-27-FDXXE6XRK45 was screened as a target molecule by high-throughput sequencing in three pairs of GC tissues. RNA quantitative reverse transcription PCR was conducted to detect the expression levels of tRF-27-FDXXE6XRK45. Agarose gel electrophoresis, Sanger sequencing, cytoplasmic and nuclear RNA isolation assays, gradient dilution experiments, and room temperature and repeated freeze-thaw experiments were used to assess the detection performance of tRF-27-FDXXE6XRK45. Using the chi-square test to analyze the correlation between tRF-27-FDXXE6XRK45 expression levels and clinicopathological parameters. In addition, receiver operating characteristic curves were used to evaluate the diagnostic value of tRF-27-FDXXE6XRK45 in GC. Results: tRF-27-FDXXE6XRK45 expression levels, significantly upregulated in tissues and sera of GC patients and decreased after radical GC surgery, were correlated with the degree of differentiation, depth of tumor infiltration, TNM stage, lymph node metastasis, and nerve/vascular invasion. In comparison with current GC diagnostic markers, tRF-27-FDXXE6XRK45 displayed better efficacy. Conclusions: tRF-27-FDXXE6XRK45, with high diagnostic efficacy, can distinguish GC patients from gastritis patients and healthy donors, suggesting that tRF-27-FDXXE6XRK45 may be a promising candidate as a diagnostic marker for GC.

Gastric cancer (GC) is a common malignant digestive system tumor. Since the early symptoms of GC are usually vague and the positive rate of common biomarkers of GC is low, it is of urgent need to find new biomarkers with good sensitivity and specificity to screen and diagnose GC patients. The tRNA-derived small RNAs (tsRNAs) are emerging small noncoding RNAs that play an essential role in cancer progression. In this study, we explored whether novel tsRNAs have the potential to serve as biomarkers for GC. Three tsRNAs significantly upregulated in GC were screened by the tsRFun database. The expression level of tRF-29-R9J8909NF5JP was detected by real-time fluorescence quantitative polymerase chain reaction. Agarose gel electrophoresis and Sanger sequencing were used to verify the characteristics of tRF-29-R9J8909NF5JP. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of tRF-29-R9J8909NF5JP. The χ2 test was used to analyze the correlation between tRF-29-R9J8909NF5JP expression level and clinicopathological parameters. Kaplan-Meier survival curves were used to analyze the correlation between tRF-29-R9J8909NF5JP expression levels and survival time of GC patients. In this study, the expression level of tRF-29-R9J8909NF5JP was significantly increased in GC tissues. The expression level of tRF-29-R9J8909NF5JP was considerably higher in the serum of GC patients than in the serum of gastritis patients and in the serum of healthy donors, and the expression level of tRF-29-R9J8909NF5JP was significantly decreased in the serum of GC patients after surgery. In addition, the χ2 test showed that the expression level of tRF-29-R9J8909NF5JP in GC serum was correlated with differentiation grade, T-stage, lymph node metastasis, tumor node metastasis stage, and neurological/vascular invasion. The results of the survival curve showed that the high expression of serum tRF-29-R9J8909NF5JP was associated with a low survival rate. ROC analysis showed that serum tRF-29-R9J8909NF5JP had higher diagnostic efficiency than common GC biomarkers, and the diagnostic efficiency was further improved by combining them. At the end of the study, we predicted the downstream of tRF-29-R9J8909NF5JP. The expression level of tRF-29-R9J8909NF5JP in the serum of GC patients can effectively identify GC patients and has higher efficacy than conventional biomarkers. In addition, serum tRF-29-R9J8909NF5JP can monitor the postoperative condition of GC patients, suggesting that it has the potential to become a biomarker for GC.

G-protein-coupled receptors (GPCRs) are the most prominent family of cell surface receptors, which can regulate various biological functions and play an essential role in many diseases. GPR176 is a member of the GPCRs family and has been rarely studied in cancer. We aim to investigate the diagnostic and prognostic value of GPR176 in gastric cancer (GC) and explore its potential mechanism. Through the TCGA database and real-time quantitative PCR, we found that the expression level of GPR176 was significantly increased in GC and had good value in the diagnosis and prognosis of GC. Vitro experiments revealed that GPR176 could promote the proliferation, migration, and invasion of GC cells and may be involved in regulating multiple tumors and immune-related signaling pathways. In addition, we found that GPR176 is associated with GC immune infiltration and may affect the immune efficacy of GC patients. In summary, the high GPR176 expression level was associated with poor prognosis, more robust immune infiltration, and worse immunotherapy efficacy in GC patients, suggesting that GPR176 may be an immune-related biomarker for GC that can promote the proliferation, migration, and invasion of GC cells.

With the development of sequencing technology, transfer RNA (tRNA)-derived small RNAs (tsRNAs) have received extensive attention as a new type of small noncoding RNAs. Based on the differences in the cleavage sites of nucleases on tRNAs, tsRNAs can be divided into two categories, tRNA halves (tiRNAs) and tRNA-derived fragments (tRFs), each with specific subcellular localizations. Additionally, the biogenesis of tsRNAs is tissue-specific and can be regulated by tRNA modifications. In this review, we first elaborated on the classification and biogenesis of tsRNAs. After summarizing the latest mechanisms of tsRNAs, including transcriptional gene silencing, post-transcriptional gene silencing, nascent RNA silencing, translation regulation, rRNA regulation, and reverse transcription regulation, we explored the representative biological functions of tsRNAs in tumors. Furthermore, this review summarized the clinical value of tsRNAs in cancers, thus providing theoretical support for their potential as novel biomarkers and therapeutic targets.